• 제목/요약/키워드: Stream Query Processing

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Techniques of XML Fragment Stream Organization for Efficient XML Query Processing in Mobile Clients (이동 클라이언트에서 효율적인 XML 질의 처리를 위한 XML 조각 스트림 구성 기법)

  • Ryu, Jeong-Hoon;Kang, Hyun-Chul
    • The Journal of Society for e-Business Studies
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    • v.14 no.4
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    • pp.75-94
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    • 2009
  • Since XML emerged as a standard for data exchange on the web, it has been established as a core component in e-Commerce and efficient query processing over XML data in ubiquitous computing environment has been also receiving much attention. Recently, the techniques were proposed whereby an XML document is fragmented into XML fragments to be streamed and the mobile clients receive the stream while processing queries over it. In processing queries over an XML fragment stream, the average access time significantly depends on the order of fragments in the stream. As such, for query performance, an efficient organization of XML fragment stream is required as well as the indexing for energy-efficient query processing due to the reduction of tuning time. In this paper, a technique of XML fragment stream organization based on query frequencies, fragment size, fragment access frequencies, and an active XML-based indexing scheme are proposed. Through implementation and performance experiments, our techniques were shown to be efficient compared with the conventional XML fragment stream organizations.

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Efficient Processing of an Aggregate Query Stream in MapReduce (맵리듀스에서 집계 질의 스트림의 효율적인 처리 기법)

  • Choi, Hyunjean;Lee, Ki Yong
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.2
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    • pp.73-80
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    • 2014
  • MapReduce is a widely used programming model for analyzing and processing Big data. Aggregate queries are one of the most common types of queries used for analyzing Big data. In this paper, we propose an efficient method for processing an aggregate query stream, where many concurrent users continuously issue different aggregate queries on the same data. Instead of processing each aggregate query separately, the proposed method processes multiple aggregate queries together in a batch by a single, optimized MapReduce job. As a result, the number of queries processed per unit time increases significantly. Through various experiments, we show that the proposed method improves the performance significantly compared to a naive method.

Efficient Query Indexing for Short Interval Query (짧은 구간을 갖는 범위 질의의 효율적인 질의 색인 기법)

  • Kim, Jae-In;Song, Myung-Jin;Han, Dae-Young;Kim, Dae-In;Hwang, Bu-Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.4
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    • pp.507-516
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    • 2009
  • In stream data processing system, generally the interval queries are in advance registered in the system. When a data is input to the system continuously, for realtime processing, a query indexing method is used to quickly search queries. Thus, a main memory-based query index with a small storage cost and a fast search time is needed for searching queries. In this paper, we propose a LVC-based(Limited Virtual Construct-based) query index method using a hashing to meet the both needs. In LVC-based query index, we divide the range of a stream into limited virtual construct, or LVC. We map each interval query to its corresponding LVC and the query ID is stored on each LVC. We have compared with the CEI-based query indexing method through the simulation experiment. When the range of values of input stream is broad and there are many short interval queries, the LVC-based indexing method have shown the performance enhancement for the storage cost and search time.

A GEOSENSOR FILTER FOR PROCESSING GEOSENSOR QUERIES ON DATA STREAMS

  • Lee, Dong-Gyu;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.119-121
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    • 2008
  • Pattern matching is increasingly being employed in various researches as health care service, RFID-based system, facility management, and surveillance. Geosensor filter correlates a data stream to match specific patterns in distribution environments. In this paper, we present a geosensor query language to represent efficiently declarative geosensor query. Geosensor operators are proposed to use for fast query processing in terms of spatial and temporal area in distribution environments. We also propose a geosensor filter to match new query predicates into incoming stream predicates. Our filter can reduce the volume of transmission data and save power consumption of sensors. It can be utilized the stream data mining system to process in real-time various data as location, time, and geosensor information in distribution environments.

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Efficient Labeling Scheme for Query Processing over XML Fragment Stream in Wireless Computing (무선 환경에서 XML 조각 스트림 질의 처리를 위한 효율적인 레이블링 기법)

  • Ko, Hye-Kyeong
    • The KIPS Transactions:PartD
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    • v.17D no.5
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    • pp.353-358
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    • 2010
  • Unlike the traditional databases, queries on XML streams are restricted to a real time processing and memory usage. In this paper, a robust labeling scheme is proposed, which quickly identifies structural relationship between XML fragments. The proposed labeling scheme provides an effective query processing by removing many redundant operations and minimizing the number of fragments being processed. In experimental results, the proposed labeling scheme efficiently processes query processing and optimizes memory usage.

A FRAMEWORK FOR QUERY PROCESSING OVER HETEROGENEOUS LARGE SCALE SENSOR NETWORKS

  • Lee, Chung-Ho;Kim, Min-Soo;Lee, Yong-Joon
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.101-104
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    • 2007
  • Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

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Causality join query processing for data stream by spatio-temporal sliding window (시공간 슬라이딩윈도우기법을 이용한 데이터스트림의 인과관계 결합질의처리방법)

  • Kwon, O-Je;Li, Ki-Joune
    • Spatial Information Research
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    • v.16 no.2
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    • pp.219-236
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    • 2008
  • Data stream collected from sensors contain a large amount of useful information including causality relationships. The causality join query for data stream is to retrieve a set of pairs (cause, effect) from streams of data. A part of causality pairs may however be lost from the query result, due to the delay from sensors to a data stream management system, and the limited size of sliding windows. In this paper, we first investigate spatial, temporal, and spatio-temporal aspects of the causality join query for data stream. Second, we propose several strategies for sliding window management based on these observations. The accuracy of the proposed strategies is studied by intensive experiments, and the result shows that we improve the accuracy of causality join query in data stream from simple FIFO strategy.

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Design and Implementation of Advanced Traffic Monitoring System based on Integration of Data Stream Management System and Spatial DBMS

  • Xia, Ying;Gan, Hongmei;Kim, Gyoung-Bae
    • Journal of Korea Spatial Information System Society
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    • v.11 no.2
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    • pp.162-169
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    • 2009
  • The real-time traffic data is generated continuous and unbounded stream data type while intelligent transport system (ITS) needs to provide various and high quality services by combining with spatial information. Traditional database techniques in ITS has shortage for processing dynamic real-time stream data and static spatial data simultaneously. In this paper, we design and implement an advanced traffic monitoring system (ATMS) with the integration of existed data stream management system (DSMS) and spatial DBMS using IntraMap. Besides, the developed ATMS can deal with the stream data of DSMS, the trajectory data of relational DBMS, and the spatial data of SDBMS concurrently. The implemented ATMS supports historical and one time query, continuous query and combined query. Application programmer can develop various intelligent services such as moving trajectory tracking, k-nearest neighbor (KNN) query and dynamic intelligent navigation by using components of the ATMS.

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Spatio-temporal Query Processing Systems for Ubiquitous Environments

  • Kim, Jeong Joon;Kang, Jeong Jin;Rothwell, Edward J.;Lee, Ki Young
    • International Journal of Internet, Broadcasting and Communication
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    • v.5 no.2
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    • pp.1-4
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    • 2013
  • With the recent development of the ubiquitous computing technology, there are increasing interest and research in technologies such as sensors and RFID related to information recognition and location positioning in various ubiquitous fields. Especially, RTLS (Real-Time Locating Services) dealing with spatio-temporal data is emerging as a promising technology. For these reasons, the ISO/IEC published RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and implemented Spatio-temporal Query Processing Systems for efficiently managing and searching the incoming Spatio-temporal data stream of moving objects. Spatio-temporal Query Processing Systems's spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. Web Server uses the SOAP(Simple Object Access Protocol) message between client and server for interoperability and translates client's SOAP message into CQL(Continuous Query Language) of the spatio-temporal middleware.

Partition-based Operator Sharing Scheme for Spatio-temporal Data Stream Processing (시공간 데이터 스트림 처리를 위한 영역 기반의 연산자 공유 기법)

  • Chung, Weon-Il;Kim, Young-Ki
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.12
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    • pp.5042-5048
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    • 2010
  • In ubiquitous environments, many continuous query processing techniques make use of operator network and sharing methods on continuous data stream generated from various sensors. Since similar continuous queries with the location information intensively occur in specific regions, we suggest a new operator sharing method based on grid partition for the spatial continuous query processing for location-based applications. Due to the proposed method shares moving objects by the given grid cell without sharing spatial operators individually, our approach can not only share spatial operators including similar conditions, but also increase the query processing performance and the utilization of memory by reducing the frequency of use of spatial operators.